"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


a				={'configuration_reformer': ['REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ReformerConfig']}

try:
	if not is_sentencepiece_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a				=['ReformerTokenizer']

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a				=['ReformerTokenizerFast']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a				=[
	    'REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'ReformerAttention',
	    'ReformerForMaskedLM',
	    'ReformerForQuestionAnswering',
	    'ReformerForSequenceClassification',
	    'ReformerLayer',
	    'ReformerModel',
	    'ReformerModelWithLMHead',
	    'ReformerPreTrainedModel',
	]


if TYPE_CHECKING:
	from .configuration_reformer import REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, ReformerConfig

	try:
		if not is_sentencepiece_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_reformer import ReformerTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_reformer_fast import ReformerTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_reformer import (
		    REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    ReformerAttention,
		    ReformerForMaskedLM,
		    ReformerForQuestionAnswering,
		    ReformerForSequenceClassification,
		    ReformerLayer,
		    ReformerModel,
		    ReformerModelWithLMHead,
		    ReformerPreTrainedModel,
		)

else:
	import sys

	a				=_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



"""simple docstring"""


def      lowerCamelCase_					(   __lowerCAmelCase							)				->   "list[int]":




						'''simple docstring'''



						if upper_limit < 0:
												raise ValueError("Limit for the Catalan sequence must be ≥ 0"							)

						lowerCamelCase__   =[0] * (upper_limit + 1)

						# Base case: C(0) = C(1) = 1
						lowerCamelCase__   =1
						if upper_limit > 0:
												lowerCamelCase__   =1

						# Recurrence relation: C(i) = sum(C(j).C(i-j-1)), from j = 0 to i
						for i in range(2  ,       upper_limit + 1							):
												for j in range(__lowerCAmelCase							):
																		catalan_list[i] += catalan_list[j] * catalan_list[i - j - 1]

						return catalan_list


if __name__ == "__main__":
	print('\n********* Catalan Numbers Using Dynamic Programming ************\n')
	print('\n*** Enter -1 at any time to quit ***')
	print('\nEnter the upper limit (≥ 0) for the Catalan number sequence: ', end='')
	try:
		while True:
			a				=int(input().strip())
			if N < 0:
				print('\n********* Goodbye!! ************')
				break
			else:
				print(F'''The Catalan numbers from 0 through {N} are:''')
				print(catalan_numbers(N))
				print('Try another upper limit for the sequence: ', end='')
	except (NameError, ValueError):
		print('\n********* Invalid input, goodbye! ************\n')

	import doctest

	doctest.testmod()


